人类脑电图的单次试验地形分析:事件相关电位的新“图像”

M. De Lucia, C. Michel, S. Clarke, M. Murray
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引用次数: 15

摘要

我们提出了一种新的方法来分析单试验脑电图(EEG)数据,利用地形信息。该方法允许使用记录的所有电极来可视化事件相关电位,克服了以前需要电极选择和波形滤波的方法的问题。我们将这种方法应用于来自听觉对象识别实验的脑电图数据,我们之前在ERP水平上分析了这些数据。在统计上确定了时间结构周期,其中给定的地形占主导地位,而没有任何关于时间行为的先验信息。除了为脑电图分析提供新的方法外,数据表明,在地形检查时,在单次试验水平上可以可靠地观察到erp。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Single-trial topographic analysis of human EEG: A new `image' of event-related potentials
We present a novel approach for analyzing single-trial electroencephalography (EEG) data, using topographic information. The method allows for visualizing event-related potentials using all the electrodes of recordings overcoming the problem of previous approaches that required electrode selection and waveforms filtering. We apply this method to EEG data from an auditory object recognition experiment that we have previously analyzed at an ERP level. Temporally structured periods were statistically identified wherein a given topography predominated without any prior information about the temporal behavior. In addition to providing novel methods for EEG analysis, the data indicate that ERPs are reliably observable at a single-trial level when examined topographically.
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